Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN: 9780133594140
Author: James Kurose, Keith Ross
Publisher: PEARSON
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[画像:A strain gauge is a device that measures elongation and is used to infer forces. A gauge has been bonded to a steel beam, and is being calibrated. The resistance of the strain gauge is converted into a voltage appearing on a meter. Known forces (X, in kN) are applied, and voltmeter measurements (Y, in V) are as follows: X 6 7 8 9 10 1 2 3 4 5 11 12 13 14 Y 4.4 4.9 6.4 7.3 | 8.8 || 10.3 | 11.7 || 13.2 || 14.8 || 15.3 || 16.5 || 17.2 || 18.9| 19.3 (a) Fit a linear regression line Y = â +6X through the data and estimate the tension (force) in the beam when the meter reading is 13.8 V. Plot your results with the fitted line superimposed. Hint: Use polyfit for the fitting & polyval for the evaluation. (b) Estimate the residual standard deviation, Sg and find a 95% confidence interval for the regression slope. Is this slope statistically different from zero? What simplifica- tion can we make if it is? Hint: The 100(1-a) % confidence interval for the regression slope b is given by bta/2n-21 where SE is the standard deviation of the residual errors, and Sx is the standard deviation of the z-data. S || || Σ HIE SE Sx √n-2 1 (34-3x)2 Σ(x1 - x)2 = 22 (2)2]
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Transcribed Image Text:A strain gauge is a device that measures elongation and is used to infer forces. A gauge has been bonded to a steel beam, and is being calibrated. The resistance of the strain gauge is converted into a voltage appearing on a meter. Known forces (X, in kN) are applied, and voltmeter measurements (Y, in V) are as follows: X 6 7 8 9 10 1 2 3 4 5 11 12 13 14 Y 4.4 4.9 6.4 7.3 | 8.8 || 10.3 | 11.7 || 13.2 || 14.8 || 15.3 || 16.5 || 17.2 || 18.9| 19.3 (a) Fit a linear regression line Y = â +6X through the data and estimate the tension (force) in the beam when the meter reading is 13.8 V. Plot your results with the fitted line superimposed. Hint: Use polyfit for the fitting & polyval for the evaluation. (b) Estimate the residual standard deviation, Sg and find a 95% confidence interval for the regression slope. Is this slope statistically different from zero? What simplifica- tion can we make if it is? Hint: The 100(1-a) % confidence interval for the regression slope b is given by bta/2n-21 where SE is the standard deviation of the residual errors, and Sx is the standard deviation of the z-data. S || || Σ HIE SE Sx √n-2 1 (34-3x)2 Σ(x1 - x)2 = 22 (2)2
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